Obstructive sleep apnea syndrome detection based on ballistocardiogram via machine learning approach-Reference-Cited by-同舟云学术

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Obstructive sleep apnea syndrome detection based on ballistocardiogram via machine learning approach

Published:2019 Issue:5 Volume:16 Page:5672-5686
ISSN:1551-0018
Container-title:Mathematical Biosciences and Engineering
language:en
Short-container-title:

Author:

Gao Weidong, ,Xu Yibin,Li Shengshu,Fu Yujun,Zheng Dongyang,She Yingjia,

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

Applied Mathematics,Computational Mathematics,General Agricultural and Biological Sciences,Modelling and Simulation,General Medicine

Reference4 articles.

1. A. S. M. Shamsuzzaman, B. J. Gersh and V. K. Somers, Obstructive Sleep

2. B. Majdi, M. Hlaing and T. Lakshman, Apnea

3. P. Corbishley and E. Rodriguez-Villegas, Breathing

4. S. Akselrod, D. Gordon, F. Ubel, et al., Power spectrum analysis of heart rate

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1. Changepoint Detection in Heart Rate Variability Indices in Older Patients Without Cancer at End of Life Using Ballistocardiography Signals: Preliminary Retrospective Study;JMIR Formative Research;2024-02-12

2. Introduction to biomedical signals and biomedical imaging;Advances in Artificial Intelligence;2024

3. Changepoint Detection in Heart Rate Variability Indices in Older Patients Without Cancer at End of Life Using Ballistocardiography Signals: Preliminary Retrospective Study (Preprint);2023-10-10

4. Application of artificial intelligence in the diagnosis of sleep apnea;Journal of Clinical Sleep Medicine;2023-07

5. Contactless screening for sleep apnea with breathing vibration signals based on modified U-Net;Sleep Medicine;2023-07

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